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Les masculinités sensibles, émancipation ou adaptation ? une enquête sociologique et filmique au coeur de collectifs masculins contemporains en France et au Québec

2021· dissertation· W7149643689 on OpenAlexaboutno aff
Émilie Fernandez

Bibliographic record

Venuenot available
Typedissertation
Language
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Power (physics)Ethnography

Abstract

fetched live from OpenAlex

LES MASCULINITES SENSIBLES est une recherche sociologique qui propose d’enrichir les rares études critiques sur les hommes et les masculinités au prisme des rapports sociaux de sexe et de genre. A travers un voyage en France et au Québec, ce mémoire appelle à ressentir les différents éléments et les processus qui façonnent les identités de genre. C’est une invitation au cœur de collectifs contemporains issus d’univers singuliers dans le secteur du travail social, du milieu en développement personnel, du milieu militant queer ou encore de la scène artistique. Cette recherche explore les raisons qui poussent des hommes et des masculinités à se rassembler pour partager un travail réflexif qui les amènent à définir collectivement des formes de masculinités idéales et inspirantes. On y découvrira de multiples expériences émotionnelles et corporelles éprouvés par ces collectifs qui dessinent ainsi une forte motivation à se distinguer de la masculinité hégémonique virile, et que cette étude propose d’interpréter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.036
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.178
GPT teacher head0.460
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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